The Position
Title : AI / ML & Digital Quality & Compliance Lead (Compliance Lead)
Department : Quality, Pharma Technical Operations
Duration : Regular Full-Time Role
Type : Individual Contributor Role
Primary Location : Mississauga
Secondary Locations : San Francisco, Basel, Indianapolis
Number of Positions : 1
Who We Are
At Roche, we strive to deliver 3-5x more benefits to our patients at half the cost to society as part of our 2030 Pharma vision.
As the recently formed global Computer Systems Quality Assurance (CSQA) chapter within the Pharma Technical Operations (PT) Quality organization, we enable the delivery of regulatory-compliant digital solutions with our customers to bring actionable insights and leadership for compliant outcomes for Pharma Technical Operations (PT). Key accountabilities include :
Enabling delivery of compliant digital systems
Ownership of the Global GMP Inventory of Computerized Systems
Global Computer System Validation Oversight and CSA Oversight within Pharma Technical
Engaging with Local / Site Validation SMEs and Leaders
In CSQA , we partner across major global business functions – PTQ, PT Digital & Operational Excellence (PTE), PT-Development, PT-Regulatory, and PT-Manufacturing, and our partners in Global Informatics. Together, we will build a solid cross-functional and inclusive community, put the power of data into the hands of our people, further develop Lean and Digital skills across PT, and scale up our Digital and Advanced Analytics solutions for the benefit of our colleagues and patients.
Do you bring experience in implementing or enabling the qualifications of digital solutions, preferably in the pharma industry, and are you looking for an impactful role? We seek an individual with excellent knowledge of the pharma data ecosystem, informatics systems, tools, and techniques with a focus on quality and compliance.
What We Are Looking For
We are looking for an experienced AI / ML & Digital Quality Lead to provide Quality Assurance guidance while designing and implementing cutting-edge AI / ML / Digital solutions in a GMP Environment. If you have a passion for innovation and a proven track record in implementing AI / ML systems, this role is made for you.
As the AI / ML Systems Quality Lead, you will work with the business, data scientists, and IT to design and implement an Artificial Intelligence and Machine Learning (AI / ML) Systems Governance Framework to support GMP business objectives. You will work closely with the software development and data science teams to design, build, and implement AI / ML models that are accurate, efficient, scalable, secure, and validated for GMP use.
Your Accountabilities :
You work closely with stakeholders to identify business needs and requirements and propose technical solutions leveraging AI / ML technologies.
Develop and maintain a comprehensive understanding of the organization's technical landscape, data infrastructure, and data processing pipelines.
Lead the design and implementation of AI / ML systems that are accurate, efficient, scalable, and secure.
Work with the data science team to identify the appropriate algorithms and models for specific business problems and implement them in production systems.
Work with the software development team to integrate AI / ML systems with existing business applications and data systems.
Develop and maintain documentation for AI / ML systems, including technical specifications, system architecture diagrams, and user guides.
Ensure that AI / ML systems comply with relevant regulatory requirements, such as data privacy laws and industry standards.
Keep current with emerging AI / ML and advanced digital technologies, and assess their potential impact on the organization's technical landscape.
The Mindsets we're looking for :
The successful candidate will have — and be passionate about encouraging others to adopt :
A mindset of inclusivity
A mindset of speaking-up
A mindset of coaching others
A mindset of focusing on outcomes
A mindset of continuous learning
A mindset of shared accountability
Who You Are :
BS / MS degree or equivalent in Science or Engineering Field, with years of experience in a regulated industry, such as the pharma / biotech or medical device industry, commensurate with grade level
4+ years of relevant work experience OR
An equivalent mix of education and work experience is required
Experience in designing and / or implementing AI / ML / Adavanced Digital Analytic systems in a commercial environment.
Strong knowledge of AI / ML technologies, including deep learning, natural language processing, and computer vision.
Knowledge of Pharmaceutical Regulations (FDA / EMA) and how they relate to computerized systems (Part 11 / Annex 11 Computer Systems Validation)
Strong knowledge of programming languages such as Python, R, Julia, etc..
Strong knowledge of data processing and storage technologies such as Hadoop, Spark, and NoSQL databases.
Experience with cloud computing platforms such as AWS, Azure, or Google Cloud Platform.
ML Ops experience : model tracking and governance, multiple models in different production contexts, etc.
Excellent problem-solving and analytical skills, with the ability to identify and solve complex technical problems.
Excellent communication and collaboration skills, with the ability to work effectively with stakeholders across the organization.
Strong leadership skills, with the ability to lead a team of technical professionals.
Diverse technical experience, including AI model development, software engineering, regulated software quality and risk management, and monitoring of deployed software.
Experience with data modeling and data exploration tools, including expertise in the use of scientific computing and data management packages, is required.
A demonstrated ability to provide vision and guidance at an institutional or enterprise level.
Exceptional human relations and communication (written, verbal, and listening) skills will be necessary to communicate across disciplines and stakeholders effectively.
Understand working in a compliance-based and regulated environment, including building, deploying, and supporting secure software throughout the AI development life cycle.
Experience with quality systems regulation is required—additional experience with applicable ISO standards is desired.